This disclosure is directed to system and methods using an automated tag migration strategy to improve Image Quality (IQ), and/or to modify IQ according to a user's desires or requirements, of an image produced in an image forming device.
IQ for images formed in image forming devices is dependent on a number of complex and varyingly related factors. Among these factors are a time lapse or number of operations performed since a most recent service, repair, or replacement of one or more replaceable components and/or consumables in the image forming device. The IQ for images produced in the image forming device often degrades over time with the age of one or more replaceable components and/or consumables. When IQ deteriorates to such an extent that service is required, individual components may be serviced and cleaned, replaceable components and/or consumables may be replaced with fresh components or consumables, and calibration may be performed. As a result, IQ for images formed in the image forming device may be returned to an original level as when the device was new, the image forming device having been considered to be returned to a “pristine” condition.
Production image forming devices produce their highest IQ level immediately after recent repair functions or after replacing old consumables such as, for example, toner, with fresh material, and/or replacing aging components that degrade over time with new units. Because IQ generally decreases over time and with usage, a number of adjustments of parameters that are controllable within the image forming device, such as those that may be controllable within, for example, a digital front end (DFE) of an electrostatic image forming device, may be manipulated in order to attempt to maintain IQ at a highest level based on a degrading condition of the components and the consumables within the image forming device.
Measures of IQ are known to be decreasing functions of time following a calibration, individual part replacement and/or based on a condition of a consumable. IQ degradation curves may be plotted as functions of one or more parameters, such as a selected halftone frequency at which the image forming device is operated. The functional relationship to any specific rendering parameter, including a selected halftone frequency is generally a depiction of a trend in IQ rather that being based on an actual measurement. These functional relationships may be depicted as a representative illustration to show a robustness versus an initial IQ trade-off for example with respect to differing rendering parameters, such as, for example, halftone frequencies, over time.
A low frequency halftone is generally least stressful to the imaging system and therefore more robust and repeatable, but has the lowest initial IQ and, slowest rate of decline over time. Highest frequency halftones produce the highest initial IQ, but they are very stressful on the image forming device and suffer from significant IQ declines over comparatively shorter periods of time relative to the low halftone frequency performance. A medium frequency halftone may have a moderate initial IQ level and moderate rate of decline. Ideally, end users seek to maximize IQ over time. This can be done by manually selecting an appropriate halftone frequency candidate.